A dual-inexact fuzzy stochastic model for water resources management and non-point source pollution mitigation under multiple uncertainties

In this research, a dual-inexact fuzzy stochastic programming (DIFSP) method was developed for supporting the planning of water and farmland use management system considering the non-point source pollution mitigation under uncertainty. The random boundary interval (RBI) was incorporated into DIFSP through integrating fuzzy programming (FP) and chance-constrained programming (CCP) approaches within an interval linear programming (ILP) framework. The lower and upper bounds of RBI are continuous random variables, and the correlation exiting between the lower and upper bounds can be tackled in RBI through the joint probability distribution function. And thus the subjectivity of decision making is greatly reduced, enhancing the stability and robustness of obtained solutions. The proposed method was then applied to solve a water and farmland use planning model (WFUPM) with non-point source pollution. The generated results could provide decision makers with detailed water supply-demand schemes involving diversified water related activities under various system conditions. These useful solutions could allow more in-depth analyses of the trade-offs between human and environment, as well as those between system optimality and reliability. In addition, comparative analyses on the solutions obtained from ICCP (Interval chance-constraints programming) and DIFSP demonstrated the higher application of this developed approach for supporting the water and farmland use system planning.